Mapping business workflows into agent tasks

Business workflows—approvals, reporting, triage, document review—often span multiple tools and people. Mapping those workflows into agent tasks means breaking each process into discrete steps an AI agent can execute: triggers, inputs, actions, and outputs. For US professionals, that includes deciding how documents and PDFs are read and passed to the agent so tasks stay reliable and auditable. This guide covers how to map business workflows into agent tasks, including where PDFs fit and how to keep execution consistent.

Summary Decompose each workflow into a trigger, a sequence of agent tasks (gather, normalize, act, deliver), and one output. When workflows depend on PDFs, use a single extraction and summarization step like iReadPDF so the agent always receives readable input and task mapping stays clear.

Table of Contents

• What “Mapping Workflows into Agent Tasks” Means
• Why Map Explicitly
• Step 1: Identify the Workflow and Its Goal
• Step 2: List Every Step and Who (or What) Does It
• Step 3: Define the Trigger and Inputs
• Step 4: Turn Steps into Agent Tasks
• Step 5: Handle Document and PDF Steps
• Step 6: Define Outputs and Failure Handling
• Conclusion

What “Mapping Workflows into Agent Tasks” Means

A business workflow is an end-to-end process: e.g., “When a contract arrives, summarize it, check key terms, and route to legal or auto-approve.” Agent tasks are the discrete units of work an AI agent (or automation) can perform: “Read inbox,” “Extract and summarize PDF,” “Classify by risk,” “Post to Slack.”

Mapping workflows into agent tasks means:

• Decomposing the workflow into a sequence of steps.
• Assigning each step to the agent (automatic) or to a human (review, approve).
• Defining triggers (what starts the workflow) and outputs (where results go).
• Normalizing document handling so any step that needs PDF content receives it in a consistent form (e.g., text or summary from iReadPDF), not raw files.

When mapping is done well, the agent has a clear list of tasks, each with known inputs and outputs, and document-heavy steps don’t break the pipeline.

Why Map Explicitly

Without explicit mapping:

• Steps are vague (“review the contract”) and the agent or human doesn’t know exactly what to do.
• Document handling is ad hoc—sometimes the agent gets a PDF, sometimes a summary, and behavior varies.
• Failures are hard to trace because it’s unclear which task failed and what the input was.

With explicit mapping:

• Each agent task has a name, input, action, and output. You can log, test, and debug at the task level.
• Document steps are one task: “Extract and summarize PDF from [source].” The next task always receives the same kind of input.
• You can improve or replace individual tasks (e.g., a better extraction tool) without redoing the whole workflow.

For US teams, explicit mapping also supports compliance and audit: you can show what the agent did, what it read, and what it produced.

Step 1: Identify the Workflow and Its Goal

Start with one workflow and one goal.

• Workflow: e.g., “Contract intake and routing.”
• Goal: e.g., “Every contract PDF is summarized, classified, and either auto-routed or queued for legal review within one hour.”

Write the goal in one sentence. That becomes the success criterion for the whole mapping: every task should contribute to that outcome. If the workflow involves documents (contracts, reports, invoices), note that the goal depends on reliable reading and summarizing of those documents—which you’ll formalize as an agent task later.

Step 2: List Every Step and Who (or What) Does It

List every step in the current process, in order. For each step, note whether it’s done by a person, a system, or could be done by an agent.

| Step | Who does it today | Agent can do it? | |------|-------------------|------------------| | 1. Get new contract (email or folder) | System / person | Agent (trigger + fetch) | | 2. Read and summarize the PDF | Person | Agent (with extraction tool) | | 3. Check key terms (dates, parties) | Person | Agent (parse from summary) | | 4. Decide: auto-approve or send to legal | Person | Agent (rule-based) or human | | 5. Send to legal queue or post result | Person | Agent (API or message) |

Steps that are “read the PDF” or “summarize the report” become a single agent task once you have a consistent extraction step—e.g., iReadPDF for OCR and summarization—so the agent never has to “read” raw PDFs, only work with text or summaries.

Step 3: Define the Trigger and Inputs

Decide what starts the workflow and what the inputs are.

• Trigger: Schedule (e.g., “every hour”), event (e.g., “new email in label Contracts,” “new file in folder”), or webhook. One trigger per workflow keeps mapping clear.
• Inputs: Exactly what the first task receives. “All PDF attachments from emails in label Contracts in the last hour,” or “All PDFs in folder /inbox/contracts.” Be specific so the agent and your logs are deterministic.

If the workflow is document-centric, the trigger often is “new document” and the first input is the document (or its path/URL). The first agent task then is “extract and summarize this document” so every later task gets normalized input.

Step 4: Turn Steps into Agent Tasks

Convert each step into an agent task with:

• Task name. Short and unique (e.g., extract_summarize_pdf, classify_contract, post_to_slack).
• Input. What this task receives (e.g., “path to PDF” or “summary text from previous task”).
• Action. What the agent does (e.g., “Call extraction API,” “Parse dates and parties from summary,” “If risk = low then route to auto-approve else queue for legal”).
• Output. What this task produces for the next task or for the final destination (e.g., “Summary text,” “Classification + key terms,” “Message posted”).

Order tasks in sequence. If a task needs document content, its input should be the output of the extraction task—never the raw PDF. That way, mapping business workflows into agent tasks stays consistent and the agent always works with the same kind of input for “read” steps.

Step 5: Handle Document and PDF Steps

Whenever a step involves reading or summarizing a PDF:

1. Create one agent task for extraction. Input: path or file. Action: run OCR and summarization (e.g., with iReadPDF). Output: plain text or structured summary. All downstream tasks take their input from this output, not from the PDF.
2. Use one tool for all PDFs. Don’t mix “summarize with tool A” and “summarize with tool B.” One tool (e.g., iReadPDF) keeps behavior consistent and makes it easy to swap or upgrade in one place. iReadPDF runs in the browser and keeps files on your device, which fits US privacy and data-residency needs.
3. Don’t give the agent raw PDFs for “reading.” The agent task should be “use this summary” or “parse this text,” not “interpret this binary.” That keeps task boundaries clear and avoids variability from format or scan quality.

If the workflow runs on a server, the extraction task may call an API or script that uses your chosen tool; the important part is that the rest of the task map consumes only the extraction output.

Step 6: Define Outputs and Failure Handling

• Final output. Where does the workflow deliver? (Slack channel, email, CRM, ticket system.) Define the format (e.g., “One message per contract with summary and route decision”) so the last agent task has a clear target.
• Per-task failure. If a task fails (e.g., extraction timeout, missing file), what happens? Options: retry N times, skip and log, or abort and alert. For extraction tasks, standardizing on one tool reduces failure modes and makes retry/alert logic simpler.
• Logging. Log trigger, each task’s input (e.g., file ID, not full content), and outcome. That gives you an audit trail and makes it easy to see which task failed when something goes wrong.

When documents are involved, log which files were processed and whether extraction succeeded; keep full content out of shared logs for privacy and compliance.

Conclusion

Mapping business workflows into agent tasks means decomposing each process into a trigger, a sequence of tasks with clear inputs and outputs, and one final destination. When workflows depend on PDFs, add a single extraction and summarization task—using a tool like iReadPDF—so the agent always receives readable input and task boundaries stay clear. For US professionals, that produces reliable, auditable automation with document-heavy steps under control.

Ready to map your document workflows into agent tasks? Use iReadPDF to extract and summarize PDFs so your agents get accurate, consistent input every time.